o i@sVdZddlZddddddd ZGd d d eZd d Z  dddZ  dddZdS)z- A vendored copy of scipy.optimize.fminbound.Nz%Optimization terminated successfully.z9Maximum number of function evaluations has been exceeded.z/Maximum number of iterations has been exceeded.z=Desired error not necessarily achieved due to precision loss.zNaN result encountered.z-The result is outside of the provided bounds.)successmaxfevmaxiterpr_lossnan out_of_boundsc@seZdZdZddZdS)OptimizeResultz) Represents the optimization result. c Cs.z||WSty}zt||d}~ww)N)KeyErrorAttributeError)selfnameerY/home/ubuntu/veenaModal/venv/lib/python3.10/site-packages/cupyx/scipy/signal/_optimize.py __getattr__s   zOptimizeResult.__getattr__N)__name__ __module__ __qualname____doc__rrrrrrs rcCsR|dkr|dkrtd|d|dkr|rtd|dkr'|r'tdtddS) Nrzk Optimization terminated successfully; The returned value satisfies the termination criteria (using xtol = )zO Maximum number of function evaluations exceeded --- increase maxfun argument. z {}r)printformat_status_message)xflagfvalmaxfunxtoldisprrr _endprintsr!rh㈵>rc CsJ||d}t|||f|fi|} |r!| d| d| d| dfS| dS)aUBounded minimization for scalar functions. Parameters ---------- func : callable f(x,*args) Objective function to be minimized (must accept and return scalars). x1, x2 : float or array scalar Finite optimization bounds. args : tuple, optional Extra arguments passed to function. xtol : float, optional The convergence tolerance. maxfun : int, optional Maximum number of function evaluations allowed. full_output : bool, optional If True, return optional outputs. disp : int, optional If non-zero, print messages. 0 : no message printing. 1 : non-convergence notification messages only. 2 : print a message on convergence too. 3 : print iteration results. Returns ------- xopt : ndarray Parameters (over given interval) which minimize the objective function. fval : number The function value evaluated at the minimizer. ierr : int An error flag (0 if converged, 1 if maximum number of function calls reached). numfunc : int The number of function calls made. Returns ------- xopt : ndarray Parameters (over given interval) which minimize the objective function. See also -------- scipy.optimize.fminbound Notes ----- Finds a local minimizer of the scalar function `func` in the interval x1 < xopt < x2 using Brent's method. (See `brent` for auto-bracketing.) References ---------- .. [1] Forsythe, G.E., M. A. Malcolm, and C. B. Moler. "Computer Methods for Mathematical Computations." Prentice-Hall Series in Automatic Computation 259 (1977). .. [2] Brent, Richard P. Algorithms for Minimization Without Derivatives. Courier Corporation, 2013. )xatolrrfunstatusnfev)_minimize_scalar_bounded) funcx1x2argsrr full_outputr optionsresrrr fminbound.sBr0c' KsP|}t|dkr td|\}} || krtdd} d} d} td} dd td }|| }}||||}||}}d }}|}||g|R}d }d ||f}tj}|}}d||}| t||d }d |}|dkrtdt| td|| ft|||d||krd } t||kr!d} ||||}!||||}"|||"|||!}#d |"|!}"|"d kr|# }#t|"}"|}!|}t|#td|"|!kr|#|"||kr|#|"||kr|#d |"}||}d} |||ks |||krt||||dk}$||$}nd } | r8||kr.||}n||}||}d} t||dk}$||$tt||}||g|R}|d 7}|||f}|dkrmtd|| f||kr||krz|}n|}||}}||}}||}}n3||kr|}n|}||ks||kr||}}||}}n||ks||ks||kr||}}d||}| t||d }d |}||krd } nt|||d||kst |st |st |rd} |}%|dkrt || |%|||t |%| | dkddt dd | d|||d}&|&S)a Options ------- maxiter : int Maximum number of iterations to perform. disp: int, optional If non-zero, print messages. 0 : no message printing. 1 : non-convergence notification messages only. 2 : print a message on convergence too. 3 : print iteration results. xatol : float Absolute error in solution `xopt` acceptable for convergence. rzbounds must have two elements.z(The lower bound exceeds the upper bound.rz2 Func-count x f(x) Procedurez initialgOd@s"   M